Predicting factors for extremity fracture among border-fall patients using machine learning computing.

Background: The factors causing the injuries sustained from falls at US-Mexican border include falls from border wall or fence, fleeing from border patrols, ejecting from vehicle, and others. This study aimed to determine the factors leading to anatomical injuries and to identify the importance of factors leading to limb fracture and internal organ injuries. Methods: A total of 178 patients who sustained musculoskeletal injuries or internal organ injuries and were admitted to our hospital were included in this retrospective study. Factors indexed for analysis included demographics, comorbidities, and falling mechanic factors. Correlations between anatomical injuries and mechanical injuries were analyzed. Multilayer perceptron neural network (MPNN) was used to identify predictive factors and to stratify the importance of these factors leading to injuries. The SPSS software was used for statistical analysis and predictive factor analysis. Results: The extremity fracture was associated with border wall/fence fall (p = 0.001) and fleeing (p = 0.002). The spine fracture was correlated with bridge jump/fall (p = 0.007), fence jump/fall (p = 0.026). The vehicle ejecting/MVA was correlated with head injury (P < 0.001), chest injury (P < 0.001), and abdominal injury p < 0.001). MNPP stratify the importance of factor causing injury with multiple factor considered. Conclusion: The various injury factors caused different anatomical injuries. Multifactorial assessment associated with these injuries can improve the accuracy of diagnosis and develop a predictive model for clinical applications.

Implementation of an Alcohol Screening, Brief Intervention, and a Referral Program at a Community Level II Trauma Center.

BACKGROUND: Trauma is the leading cause of years of potential life lost in the United States. Alcohol and drug use is a significant contributing factor. In 2017, a Level II community trauma center was achieving less than 80% screening rate compliance utilizing blood alcohol level as a screening method for trauma patients. The purpose of this article is to evaluate the implementation of a screening, brief intervention, and a referral-to-treatment service program. METHODS: In 2018, the trauma program adopted structured interviews as a screening method for trauma patients. The injury prevention coordinator conducted structured interviews as a screening method for trauma patients who met inclusion criteria. High-risk patients were referred to the social worker, who conducted a brief evaluation with subsequent referral to treatment. RESULTS: One year after the implementation of a structured interview approach, 1,021 trauma patients met inclusion criteria for this retrospective evaluation. From 2017 to 2018, the program observed an 86% statistically significant increase in screening using the structured interview SBIRT program (p < .0001) compared with the prior alcohol-level screening approach. CONCLUSIONS: On the basis of these data, a structured interview screening method demonstrated a significant improvement in screening compliance rates.